Real-Time detection of Plasmopara viticola sporangia using automated air-flow cytometry

Abstract

Fungal diseases such as downy mildew (Plasmopara viticola) can severely impact grapevine yield and quality, making timely-wise fungicide applications essential. For that, Decision Support Systems (DSS) in precision viticulture guide farmers on optimal timing for treatments. However, most current DSS rely mainly on weather data and overlook biological indicators such as real-time dynamics of spore concentrations within the vineyard. To address this gap, we assessed the use of an automatic air-flow cytometer (SwisensPoleno Jupiter) for the real-time detection and quantification of P. viticola sporangia. The instrument combines holographic imaging, fluorescence spectroscopy, and artificial intelligence-based classification. Laboratory measurements using naturally and artificially infected leaves provided training datasets comprise >17,000 single sporangia (events), enabling the development of classifier software using advanced AI methods. We used Random Forest models. Specificity tests of the classifier against databases of common airborne fungal spores confirmed their high accuracy in matching true with predicted labels. Field validation was conducted in Swiss vineyards using complementary approaches: Hirst-type spore traps (microscopy identification of sporangia and qPCR-based DNA quantification) and SwisensPoleno classification. Spearman correlations were calculated to compare between strategies (p < 0.5). Comparison between manual microscopy and SwisensPoleno classification began to emerge during the 2023 pilot study (60 days) and strengthened markedly throughout the 2024 monitoring season (140 days). Seasonal analyses revealed that SwisensPoleno data correlated more strongly with DNA quantification (r = 0.53) than with microscopy identification (r = 0.44). Correlations were weak early in the season, during leaf development and the onset of flowering, but strengthened as vine phenology progressed and disease pressure increased, reaching up to r = 0.94 with microscopy counting and r = 0.83 with DNA concentration. Moreover, airborne concentrations of P. viticola sporangia were strongly associated with mean daily air temperature, and daily sporangia measurements were different depending on the aerosol inlet height of the SwisensPoleno instrument. Visual disease assessments in 2024 confirmed high downy mildew pressure, affecting nearly 100% of unprotected leaves. Consequently, DNA concentrations were strongly correlated with symptom severity (r = 0.96). With further refinement, these first models for real-time and automatic identification of P. viticola sporangia have the potential to provide reliable spore monitoring data for DSS integration, supporting precision viticulture worldwide.

References

Agrometeo. (2024). Agrometeorological platform for weather and disease forecasting in Swiss agriculture. Agroscope, Switzerland. Available from: https://www.agrometeo.ch.

Buters, J., Clot, B., Galán, C., Gehrig, R., Gilge, S., Hentges, F., O’Connor, D., Sikoparija, B., Skjoth, C., Tummon, F., Adams-Groom, B., Antunes, C. M., Bruffaerts, N., Çelenk, S., Crouzy, B., Guillaud, G., Hajkova, L., Seliger, A. K., Oliver, G., … Stjepanovic, B. (2024). Automatic detection of airborne pollen: an overview. Aerobiologia, 40(1), 13–37. https://doi.org/10.1007/S10453-022-09750-X/TABLES/2

Koledenkova, K., Esmaeel, Q., Jacquard, C., Nowak, J., Clément, C., & Ait Barka, E. (2022). Plasmopara viticola the Causal Agent of Downy Mildew of Grapevine: From Its Taxonomy to Disease Management. Frontiers in Microbiology, 13, 889472. https://doi.org/10.3389/FMICB.2022.889472/FULL

La Torre, A., Talocci, S., Spera, G., & Valori, R. (2008). Control of downy mildew on grapes in organic viticulture. Communications in Agricultural and Applied Biological Sciences, 73(2), 169–178. https://pubmed.ncbi.nlm.nih.gov/19226754/

Muthukumar, G., Kamalakannan, A., Johnson, I., Kamaraj, P., Muthuvel, I., Varanavasiappan, S., & Angayarkanni, T. (2025). Early detection and quantification of airborne inocula of Plasmopara viticola causing grapevine downy mildew using impaction spore trap. Physiological and Molecular Plant Pathology, 139, 102842. https://doi.org/10.1016/J.PMPP.2025.102842

Peng, J., Wang, X., Wang, H., Li, X., Zhang, Q., Wang, M., & Yan, J. (2024). Advances in understanding grapevine downy mildew: From pathogen infection to disease management. Molecular Plant Pathology, 25(1), e13401. https://doi.org/10.1111/MPP.13401

Si Ammour, M., Bove, F., Toffolatti, S. L., & Rossi, V. (2020). A Real-Time PCR Assay for the Quantification of Plasmopara viticola Oospores in Grapevine Leaves. Frontiers in Plant Science, 11, 544169. https://doi.org/10.3389/FPLS.2020.01202/BIBTEX

Technical specification CEN/TS 16868:2015 (2015). Ambient Air – Sampling and Analysis of Airborne Pollen Grains and Fungal Spores for Allergy Networks – Volumetric Hirst Method.

Valsesia, G., Gobbin, D., Patocchi, A., Vecchione, A., Pertot, I., & Gessler, C. (2005). Development of a High-Throughput Method for Quantification of Plasmopara viticola DNA in Grapevine Leaves by Means of Quantitative Real-Time Polymerase Chain Reaction. Phytopathology, 95(6), 672–678. https://doi.org/10.1094/PHYTO-95-0672

World Organisation of Vine and Wine (OIV). (2019). Resolution OIV-Viti 593-2019.

Acknowledgments

The spore classifier pipeline was developed through collaboration in the AGRARSENSE, SYLVA, and EZSM projects. AGRARSENSE and SYLVA are supported by the EU and Switzerland’s SERI. AGRARSENSE also receives funding from the Chips Joint Undertaking and national agencies across 11 European countries. EZSM is funded by the Swiss Federal Office of Agriculture, Swisspatat, VSKP/USSPPT, Syngenta, and Fondation sur la Croix.